This study examines the birth of television and the modern media corporation that launched it, through the archives of the designer of the "first" set, John Vassos, a Greek-born American industrial designer, interior decorator, and illustrator (1898-1985). Vassos's early career is used as a case study to analyze the historical and cultural forces that shaped the emergence of this new media and the new profession of industrial design, through archival materials housed in the Archives of American Art at the Smithsonian Institution in Washington D.C. and at Syracuse University. Specifically, this thesis unites various parts of Vassos's early career, from his modernist illustrations to industrial design, through the aesthetics and practices of modernism. As RCA's lead industrial designer for over 40 years, Vassos was involved in the design and promotion of RCA's electronic products, including radios and televisions and studio equipment. Vassos also designed the new spaces carved out for their use in the home including the "living room of the future" featured at the 1939 World's Fair. Drawing from his skills as an illustrator, designer and display expert, Vassos helped develop RCA's public image at a time of its greatest expansion in radio and television manufacturing and broadcasting. This reading of Vassos's work is both diachronic, taking into account his work over the early part of his career to analyze his specific contribution and synchronic, in relationship to other designers working contemporaneously. Thus, this thesis explores Vassos's double role as a participant, with active agency within the emergence of the new field and as a subject, constrained by social roles and forces. Ranging from turnstile to the transmitter, Vassos along with other industrial designers used the streamlined aesthetic to create visual unity among mechanical and electronic products, from home to office, from subway to skyline.

Wireless systems, ranging from radio to optical frequencies, typically comprise two domains: the signal path and the local oscillator (LO) path. While signal processing is conventionally performed in the signal path, more recently, techniques that exploit LO-based signal processing are becoming increasingly popular. LO-based analog signal processing can be utilized for solving fundamental problems and for improving the performance of systems in a wide variety of applications that span radio to optical frequencies. In this dissertation, I explore LO-based signal processing to enable new functionalities and enhance performance in electrical, optical, and electro-optical circuits and systems. In the electro-optical domain, I use LO-based signal processing to improve the performance of a long-range Frequency-Modulated Continuous-Wave (FMCW) Light Detection and Ranging (LiDAR) system. As laser nonlinearity degrades the performance of ranging and imaging systems, it is essential to address this problem. In this dissertation, to linearize a laser, an integrated continuous-time Electro-Optical Phase-Locked Loop (EOPLL) is presented with a loop bandwidth equal to its reference frequency. Despite the high bandwidth, the proposed system is spurless, which is enabled by using Single-Sideband (SSB) and Harmonic-Reject mixing (HRM) techniques. These techniques are explored in Phase-Locked Loop (PLL) design for the first time. These features result in less area consumption and loss associated with the optical part of the system and increase the precision and accuracy of our long-range FMCW LIDAR significantly. In the electrical domain, I use LO engineering to address some of the challenges that exist in three different electrical systems including mm-wave Multi-Input Multi-Output (MIMO) systems, ultra-low power RF systems, and wideband mm-wave systems. In the first project, to alleviate the challenge of supporting a high data rate Input/Output (I/O) interface in a large-scale tiled mm-wave MIMO array, a single-wire interface (SWI) is used in this dissertation, and a 60GHz 4-element scalable MIMO transmitter (TX) prototype is designed. In our work, we use frequency-domain multiplexing (FDM) to simultaneously support the signals of four MIMO channels. Then, in our proposed FDM, HRM is utilized to generate the different frequencies at which the various IF signals are multiplexed. This enables us to multiplex and de-multiplex the four modulated signals simultaneously to/from the single-wire using multiple phases of only one LO. The technique proposed in this research significantly reduces the number of lines needed for LO and signal routing in a massive MIMO system. The second electrical project in this dissertation targets ultra-low power receivers at RF frequency. Wake-up receivers (WURX) are integral to reducing the power consumed by the main or primary RX in ultra-low power systems. Thus, the ability to share one antenna for both RXs is essential and results in a compact hybrid system. Furthermore, linearity and sensitivity are two fundamental criteria in these RXs. In order to improve the linearity of these systems, mixer-first RX architecture can be used for both RXs. However, mixer-first architecture has some drawbacks, like low gain and high noise figure (NF), which degrade the sensitivity of the system. Here, in our research, we implement a hybrid primary RX and WURX in which, first, a Quadrature Hybrid Coupler (QHC) is used to share one antenna between the two RXs and to achieve wideband input matching. Secondly, to address the problem of sensitivity in the mixer-first structure, we exploit a LO-assisted noise-canceling technique combined with a bottom-plate capacitor mixer-first receiver. This structure exploits implicit capacitive stacking which enables us to achieve passive LO-defined voltage gain, high linearity, and a low NF. In the last electrical project in this dissertation, I present a novel frequency-interleaved (FI) channel aggregation architecture for wideband mm-wave systems that relaxes the requirements of their Analog-to-Digital/Digital-to-Analog Converters (ADC/DAC) and consequently reduces the total cost and power consumption. In our proposed architecture, the input bandwidth is channelized into four sub-channels, which are individually up/downconverted from/to baseband, where they can be digitized with multiple lower rate subconverters. We use the idea of HRM in the channelizer to simultaneously down(up)convert four sub-channels with only one LO. Four chips, including two mm-wave RX and TX chips and two baseband RX and TX chips, are designed and tested to show the functionality of the entire system as a transceiver. Finally, I conclude this dissertation with an optical project which is a Silicon Photonic (SiP) simultaneous Mode and Wavelength Division (De)Multiplexer (MWD(De)MUX) for optical frequencies at C-band. I use an advanced 3D simulation tool, RSOFT software, to design and test this novel compact SiP structure. Our circuit uses a cascade of Mode Division Multiplexer (MDM) and Wavelength Division Multiplexer (WDM) stages for (de)multiplexing. A novel phase shifter introduced and used in this work is designed using two close waveguides on a CMOS compatible SiP platform, which results in reduced loss and size compared to conventional techniques.

Two algorithms for estimating the frequency and power of the carriers of 20 GHz and 30 GHz satellite signals are compared. Both algorithms operate on a prefiltered sequence generated by lowpass filtering followed by signal decimation for the purpose of sampling rate reduction. The lowpass filtering is accomplished via the overlap-add method of FIR filtering using the FFT. Carrier frequency prediction and tracking is accomplished with a Kalman predictor, for which the frequency drift process is modeled via polynomial extrapolation. The Kalman predictor operates on frequency measurements provided by one of two frequency estimators. One of the frequency estimation algorithms, a refinement of the DFT-automatic frequency control technique, uses the Chirp-Transform algorithm in its aim for the maximum likelihood estimate of frequency and power. The averaged periodogram is computed from the prefiltered sequence and is used to measure the frequency of the drifting frequency signal as well as its power. One of the disadvantages of this algorithm is the bias present in the estimation of power. The bias can be removed only with knowledge of the noise power. The algorithm has the advantage of being almost exclusively a convolution and therefore is accomplished with minimal computation via the FFT. An alternative parametric approach to frequency estimation is also investigated. In this approach the weighted least-squares modified Yule-Walker method of autoregressive model estimation is used on the prefiltered sequence to yield frequency estimates. Power estimation is accomplished next via modal decomposition of the estimated correlation sequence. The advantage of this approach is that for slowly varying frequency drift paths (24 hour cycle) the frequency estimates exhibit MSE approximately 3 dB less than the Chirp-Transform algorithm over a wide range of SNR. There are two disadvantages to the parametric algorithm. First the parametric algorithm estimates power with MSE approximately 2 dB greater than the nonparametric algorithm. Secondly the algorithm is more complicated than the nonparametric Chirp-Transform algorithm because it requires matrix inversions and the determination of the roots of a polynomial. For the digital beacon receiver problem investigated here both algorithms perform similarly in two important respects. First both algorithms can lock onto a carrier signal whose frequency is drifting at the rate of 5 Hertz per second in a noise environment corresponding to a 15 dB/Hz SNR. Secondly both algorithms can make unbiased frequency estimates of the carrier signal allowing the receiver to track the carrier at 7 dB/Hz SNR. Both algorithms attain the Cramer-Rao bound for estimation of constant frequency sinusoids. For a simulated satellite signal with maximum frequency drift of 5 Hertz per second the Kalman frequency predictor is able to reduce the problem to nearly that of the constant frequency case so that the resulting performance corresponds to the Cramer-Rao bound for estimation of constant frequency sinusoids. Where computational considerations are critical the nonparametric algorithm is preferred. In fact, unless the superior accuracy of the frequency prediction afforded by the parametric algorithm is paramount, the nonparametric algorithm is to be chosen. / Master of Science

Wireless sensor networks are becoming important in several monitoring and sensing applications. Ultra low power consumption in the sensor nodes is important for extending the battery life of the nodes. In this dissertation, two low power BFSK receiver architectures are proposed and verified with prototype implementations in silicion. A 2.4 GHz 1 Mb/s polyphase filter (PPF) BFSK receiver demonstrates ±180 ppm frequency offset tolerance (FOT) and 40 dB adjacent channel rejection (ACR) at a modulation index (MI) of 2, with a power consumption of 1.9 mW. High FOT at low MI is achieved by a frequency-to-energy conversion architecture using PPFs without any frequency correction. The proposed hybrid topology of the PPF provides an improved ACR at reduced power. To further improve the energy efficiency, a low energy 900 MHz mixer-less BFSK receiver is designed. High gain frequency-to-amplitude conversion and better sensitivity is achieved by a linear amplifier with Q-enhanced LC tank, eliminating the need for local oscillators and mixers. With a power consumption of 500 μW, the receiver achieves sensitivities of -90 dBm and -76 dBm for data rates of 0.5 Mb/s and 6 Mb/s, respectively. The energy efficiency is 80 pJ/b when operating at 6 Mb/s. / Graduation date: 2013 / Access restricted to the OSU Community at author's request from March 25, 2013 - March 25, 2014

Energy-efficient radio frequency (RF) power amplifiers (PAs) are critical and paramount to achieve longer battery life in state-of-the-art portable systems because they typically determine and dominate the power consumption of such devices. In this dissertation, a high-efficiency, linear RF PA with a dynamically adaptive supply and bias current control for code division multiple access (CDMA) and wideband CDMA (WCDMA) is conceived, simulated, and experimentally demonstrated with a discrete PCB-level design and in integrated circuit (IC) form. The PA efficiency is improved by dynamically adjusting both its supply voltage and bias current, there by minimizing its quiescent power dissipation. The PA supply voltage is derived from the battery by a noninverting, synchronous buck-boost switching regulator because of its flexible functionality and high efficiency. Adjusting the PA supply voltage and bias current by tracking the output power, instead of following the complete envelope in large baseband bandwidth wireless applications, is achieved by a converter with a lower switching frequency and consequently higher light-load efficiency, which translates to prolonged battery life. A discrete PCB-level prototype of the proposed system with 915 MHz center frequency, CDMA IS-95 signal having 27-dBm peak-output power resulted in more than four times improvement in the average efficiency compared to a fixed-supply class-AB PA while meeting the required performance specifications. In the IC solution fabricated in AMIs 0.5-micron CMOS process through MOSIS, a dual-mode, buck-boost converter with pulse-width modulation (PWM) control for high power and pulse-frequency modulation (PFM) for low power is designed and implemented to improve the PA efficiency during active and standby operation, respectively. The performance of the dynamically adaptive supply and bias control IC was validated by realizing a 25-dBm, 1.96 GHz center frequency, WCDMA PA over an input supply range of 1.4 4.2 V. The PA with dual-mode power supply and bias control IC showed an average-efficiency improvement of seven times compared to a fixed-supply class-AB PA, which translates to five times improvement in battery life assuming the PA is active for 2 % of the total time and in standby mode otherwise.

With the advance of the LCD technology, video quality is becoming increasingly important. In this thesis, we develop hardware-friendly low-complexity enhancement algorithms. Video quality enhancement methods can be classified into two main categories. Single frame methods are the first category. These methods have generally low computational complexity. Multi-frame methods combine information from more than one frame and require the motion information of objects in the scene to do so. We first concentrate on the contrast-enhancement problem by using both global (frame-wise) and local information derived from the image. We use the image histogram and present a regularization-based histogram modification method to avoid problems that are often created by histogram equalization. Next, we design a compression artifact reduction algorithm that reduces ringing artifacts, which is disturbing especially on large displays. Furthermore, to remove the blurriness in the original video we present a non-iterative diffusion-based sharpening algorithm, which enhances edges in a ringing-aware fashion. The diffusion-based technique works on gradient approximations in a neighborhood individually. This gives more freedom compared to modulating the high-pass filter output that is used to sharpen the edges. Motion estimation enables applications such as motion-compensated noise reduction, frame-rate conversion, de-interlacing, compression, and super-resolution. Motion estimation is an ill-posed problem and therefore requires the use of prior knowledge on motion of objects. Objects have inertia and are usually larger then pixels or a block of pixels in size, which creates spatio-temporal correlation. We design a method that uses temporal redundancy to improve motion-vector search by choosing bias vectors from the previous frame and adaptively penalizes deviations from the bias vectors. This increases the robustness of the motion-vector search. The spatial correlation is more reliable because temporal correlation is difficult to use when the objects move fast or accelerate in time, or have small sizes. Spatial smoothness is not valid across motion boundaries. We investigate using energy minimization for motion estimation and incorporate the spatial smoothness prior into the energy. By formulating the energy minimization iterations for each motion vector as the primal problem, we show that the dual problem is motion segmentation for that specific motion vector.

Cognitive radios have been proposed as a new technology to counteract the spectrum scarcity issue and increase the spectral efficiency. In cognitive radios, the sparse assigned frequency bands are opened to secondary users, provided that interference induced on the primary licensees is negligible. Cognitive radios are established in two steps: the radios firstly sense the available frequency bands by detecting the presence of primary users and secondly communicate using the bands that have been identified as not in use by the primary users.<p><p>In this thesis we investigate how to improve the efficiency of cognitive radio networks when multiple cognitive radios cooperate to sense the spectrum or control their interferences. A major challenge in the design of cooperating devices lays in the need for exchange of information between these devices. Therefore, in this thesis we identify three specific types of control information exchange whose efficiency can be improved. Specifically, we first study how cognitive radios can efficiently exchange sensing information with a coordinator node when the reporting channels are noisy. Then, we propose distributed learning algorithms allowing to allocate the primary network sensing times and the secondary transmission powers within the secondary network. Both distributed allocation algorithms minimize the need for information exchange compared to centralized allocation algorithms. / Doctorat en Sciences de l'ingénieur / info:eu-repo/semantics/nonPublished

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